diff options
Diffstat (limited to 'site/datasets/unknown/moments_in_time.json')
| -rw-r--r-- | site/datasets/unknown/moments_in_time.json | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/site/datasets/unknown/moments_in_time.json b/site/datasets/unknown/moments_in_time.json index 6522ed03..1b281272 100644 --- a/site/datasets/unknown/moments_in_time.json +++ b/site/datasets/unknown/moments_in_time.json @@ -1 +1 @@ -{"id": "41976ebc8ab76d9a6861487c97cc7fcbe3b6015f", "citations": [{"id": "a640bc0faef2c0ee44074bfd17e813d9b538bd17", "title": "Recurrent Residual Module for Fast Inference in Videos", "year": "2018", "pdf": [], "doi": ["http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8578264"]}, {"id": "2098983dd521e78746b3b3fa35a22eb2fa630299", "title": "Second-order Temporal Pooling for Action Recognition", "year": "2018", "pdf": ["https://arxiv.org/pdf/1704.06925.pdf"], "doi": []}, {"id": "2a08147bf88041c6e0354e26762b4e4d65d5163f", "title": "Trimmed Event Recognition ( Moments in Time ) : Submission to ActivityNet Challenge 2018", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/2a08/147bf88041c6e0354e26762b4e4d65d5163f.pdf"], "doi": []}, {"id": "1b71d3f30238cb6621021a95543cce3aab96a21b", "title": "Fine-grained Video Classification and Captioning", "year": "2018", "pdf": ["https://arxiv.org/pdf/1804.09235.pdf"], "doi": []}, {"id": "5eefe98aafffe665b19de515e3ba90c9c0b7219c", "title": "Trimmed Event Recognition Submission to ActivityNet Challenge 2018", "year": "", "pdf": ["https://pdfs.semanticscholar.org/5eef/e98aafffe665b19de515e3ba90c9c0b7219c.pdf"], "doi": []}, {"id": "620339aef06aed07a78f9ed1a057a25433faa58b", "title": "Human Action Recognition and Prediction: A Survey", "year": "2018", "pdf": ["https://arxiv.org/pdf/1806.11230.pdf"], "doi": []}, {"id": "878f70f6abb83f5158ca0bacfc2bacd49b1886b1", "title": "Aligning Artificial Neural Networks to the Brain Yields Shallow Recurrent Architec- Tures", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/878f/70f6abb83f5158ca0bacfc2bacd49b1886b1.pdf"], "doi": []}, {"id": "72f4c415b5f3ecf63380b6985c95c5af2ba72632", "title": "Activity Recognition on a Large Scale in Short Videos - Moments in Time Dataset", "year": "2018", "pdf": ["https://arxiv.org/pdf/1809.00241.pdf"], "doi": []}, {"id": "5a77877689e44e3ed48250f53e05b0d37bd901d7", "title": "Morph: Flexible Acceleration for 3D CNN-Based Video Understanding", "year": "2018", "pdf": [], "doi": ["http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8574597"]}, {"id": "41976ebc8ab76d9a6861487c97cc7fcbe3b6015f", "title": "Moments in Time Dataset: one million videos for event understanding", "year": "2017", "pdf": ["https://arxiv.org/pdf/1801.03150.pdf"], "doi": []}, {"id": "d3f5a1848b0028d8ab51d0b0673732cad2e3c8c9", "title": "STAIR Actions: A Video Dataset of Everyday Home Actions", "year": "2018", "pdf": ["https://arxiv.org/pdf/1804.04326.pdf"], "doi": []}, {"id": "54c7c3909c7e1e827befdbe8d2595a3b196ba1b8", "title": "AVA: A Video Dataset of Spatio-Temporally Localized Atomic Visual Actions", "year": "2018", "pdf": [], "doi": ["http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8578731"]}, {"id": "d4a8c77140ca02504c67007685c3acb1fceedb5d", "title": "SYSU iSEE submission to Moments in Time Challenge 2018", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/d4a8/c77140ca02504c67007685c3acb1fceedb5d.pdf"], "doi": []}, {"id": "86971c8a4e23aadfd20f0f609ce78a873462db63", "title": "Moments in Time : submission to ActivityNet Challenge 2018", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/8697/1c8a4e23aadfd20f0f609ce78a873462db63.pdf"], "doi": []}, {"id": "081db2f175943c51c18d0495782c1c172abd07b6", "title": "Team SSS Submission to the Moments in Time Challenge 2018", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/081d/b2f175943c51c18d0495782c1c172abd07b6.pdf"], "doi": []}, {"id": "593045f63de1273d116097eeea6fda7aa244e74d", "title": "Qiniu Submission to ActivityNet Challenge 2018", "year": "2018", "pdf": ["https://arxiv.org/pdf/1806.04391.pdf"], "doi": []}, {"id": "507f398b79e94a1ebde61c0a854c3954e7bb3d33", "title": "Non-local NetVLAD Encoding for Video Classification", "year": "2018", "pdf": ["https://arxiv.org/pdf/1810.00207.pdf"], "doi": []}, {"id": "c78008647555ebded0a196512d7dd36b78e1c0ab", "title": "The ActivityNet Large-Scale Activity Recognition Challenge 2018 Summary", "year": "2018", "pdf": ["https://arxiv.org/pdf/1808.03766.pdf"], "doi": []}, {"id": "a2f8f9ae3de0ce1a4d8976c0dd1d9ff90af80ee8", "title": "Collaborative Spatio-temporal Feature Learning for Video Action Recognition", "year": "2019", "pdf": ["https://arxiv.org/pdf/1903.01197.pdf"], "doi": []}, {"id": "cc35ca2e992f5b69e8942f2c1f7dd47714c4f272", "title": "AI Enabling Technologies", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/cc35/ca2e992f5b69e8942f2c1f7dd47714c4f272.pdf"], "doi": []}, {"id": "5b002afc3fda9ee321babab4db857c819ec5c46d", "title": "Repair Genetic Disease in Embryo", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/5b00/2afc3fda9ee321babab4db857c819ec5c46d.pdf"], "doi": []}, {"id": "a1eddece7741f0c4199989bb08326ef36b752a53", "title": "Objects Levitating with Light", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/a1ed/dece7741f0c4199989bb08326ef36b752a53.pdf"], "doi": []}, {"id": "85f957b5eaf9e2145e4271ebb05368e73d5b0d68", "title": "Muon Detector Measure Electric Potential", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/85f9/57b5eaf9e2145e4271ebb05368e73d5b0d68.pdf"], "doi": []}, {"id": "058b215d87670381ee32035b69fcc9cddda59a47", "title": "Recovering Scattered Data with SMART", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/058b/215d87670381ee32035b69fcc9cddda59a47.pdf"], "doi": []}, {"id": "362341d17940d085c983f541f1fe12b633a5ed9f", "title": "Netflix Speed Up Biological Imaging", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/3623/41d17940d085c983f541f1fe12b633a5ed9f.pdf"], "doi": []}, {"id": "5206112dbd86d62cdcd7029a7116173990428040", "title": "Next Generation Optical Tweezers", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/5206/112dbd86d62cdcd7029a7116173990428040.pdf"], "doi": []}, {"id": "bdd2ba9e8b368638c5ddb9f3070275342c14ec31", "title": "Chip Up AI Performance", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/bdd2/ba9e8b368638c5ddb9f3070275342c14ec31.pdf"], "doi": []}, {"id": "4c605da6dc4a0f487286cd4cc2c58289c862b447", "title": "Planets Discovered Using AI", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/4c60/5da6dc4a0f487286cd4cc2c58289c862b447.pdf"], "doi": []}, {"id": "8f35e4b29c77c1ddae1f315a0bba43a6f0d0a433", "title": "Artificial Intelligence Accelerates Discovery", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/8f35/e4b29c77c1ddae1f315a0bba43a6f0d0a433.pdf"], "doi": []}, {"id": "931334796221e5420c2413e35ecec69bc59a6d15", "title": "Artificial Intelligence Bring Sun Power to Earth", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/9313/34796221e5420c2413e35ecec69bc59a6d15.pdf"], "doi": []}, {"id": "c82c059e23eb9e92c814d1ac5025f5f720479679", "title": "Machine Learning Quantum Advantage", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/c82c/059e23eb9e92c814d1ac5025f5f720479679.pdf"], "doi": []}, {"id": "0e4a4f9874d4c37caa6fa63247c7e02fe160312e", "title": "Machine Learning Quantum Fireworks", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/0e4a/4f9874d4c37caa6fa63247c7e02fe160312e.pdf"], "doi": []}, {"id": "cb0e0f18e5be5c7f9307fd523d8eb680aa0fcc2a", "title": "Nanosponges for Rheumatoid Arthritis", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/cb0e/0f18e5be5c7f9307fd523d8eb680aa0fcc2a.pdf"], "doi": []}, {"id": "7e970550d48080d6ac988e069bd6c3ed5b95c325", "title": "Proteins Associated with Cancer", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/7e97/0550d48080d6ac988e069bd6c3ed5b95c325.pdf"], "doi": []}, {"id": "9091376ea8cf4d9d28c8ebaecf554ad515e0ea50", "title": "Deep Learning Human Activities", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/9091/376ea8cf4d9d28c8ebaecf554ad515e0ea50.pdf"], "doi": []}, {"id": "aa32bb2719d64d41545bf9ac9fe259833bcb14e3", "title": "Image Analysis with Deep Learning", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/aa32/bb2719d64d41545bf9ac9fe259833bcb14e3.pdf"], "doi": []}, {"id": "0aba7929b9d019bc8e1bb37827cda170a10e8d4f", "title": "Machine Learning Quantum Phases", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/0aba/7929b9d019bc8e1bb37827cda170a10e8d4f.pdf"], "doi": []}, {"id": "253fa8280c2898fcdedaca7122e749cb3e1d4b57", "title": "AI Needs Hardware Accelerators", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/253f/a8280c2898fcdedaca7122e749cb3e1d4b57.pdf"], "doi": []}, {"id": "f1c357d9543b0dc607d4222701c64deffcabc6ab", "title": "Machine Learning World ' s Oceans", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/f1c3/57d9543b0dc607d4222701c64deffcabc6ab.pdf"], "doi": []}, {"id": "02e40be81c453ea80e5e14d4a76136a804c7c90d", "title": "Faster and Simpler Deep Learning", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/02e4/0be81c453ea80e5e14d4a76136a804c7c90d.pdf"], "doi": []}, {"id": "0be47c361a25cdf188639e99b695b535f9cc662f", "title": "Nano-Electrode Detect Early Cancer", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/0be4/7c361a25cdf188639e99b695b535f9cc662f.pdf"], "doi": []}, {"id": "3e8fc0da19772f2d46af0e6d84c59d6b66be72f2", "title": "Memristor Speeding Up AI", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/3e8f/c0da19772f2d46af0e6d84c59d6b66be72f2.pdf"], "doi": []}, {"id": "ceac97bd0b90f1bacd7e43d67cb589ef5abe3e5f", "title": "Machine Learning Quantum Sensing", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/ceac/97bd0b90f1bacd7e43d67cb589ef5abe3e5f.pdf"], "doi": []}, {"id": "223afe4fad76fcec6e4f6d90b4bc2b9f45da6f4b", "title": "Cancer Reporting Machine Learning", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/223a/fe4fad76fcec6e4f6d90b4bc2b9f45da6f4b.pdf"], "doi": []}, {"id": "ba8c1fdd268c35a2d7a1fd60a101fd026f793f3e", "title": "AI Exploration of Underwater Habitats", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/ba8c/1fdd268c35a2d7a1fd60a101fd026f793f3e.pdf"], "doi": []}, {"id": "cc749cf9f26fcf07a7bde6e54f78e0592d2fd802", "title": "Deep Learning Smartphone Microscope", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/cc74/9cf9f26fcf07a7bde6e54f78e0592d2fd802.pdf"], "doi": []}, {"id": "fba86c9e8200c18ca788a4d5962853bda954bb71", "title": "Syndromes Data Mining", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/fba8/6c9e8200c18ca788a4d5962853bda954bb71.pdf"], "doi": []}, {"id": "5a29df900d1a96d4b73daa6df36b762b5f652152", "title": "AI Meets Your Shopping Experience", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/5a29/df900d1a96d4b73daa6df36b762b5f652152.pdf"], "doi": []}]}
\ No newline at end of file +{"id": "41976ebc8ab76d9a6861487c97cc7fcbe3b6015f", "citations": [{"id": "a640bc0faef2c0ee44074bfd17e813d9b538bd17", "title": "Recurrent Residual Module for Fast Inference in Videos", "year": "2018", "pdf": [], "doi": ["http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8578264"]}, {"id": "2098983dd521e78746b3b3fa35a22eb2fa630299", "title": "Second-order Temporal Pooling for Action Recognition", "year": "2018", "pdf": ["https://arxiv.org/pdf/1704.06925.pdf"], "doi": []}, {"id": "1b71d3f30238cb6621021a95543cce3aab96a21b", "title": "Fine-grained Video Classification and Captioning", "year": "2018", "pdf": ["https://arxiv.org/pdf/1804.09235.pdf"], "doi": []}, {"id": "5eefe98aafffe665b19de515e3ba90c9c0b7219c", "title": "Trimmed Event Recognition Submission to ActivityNet Challenge 2018", "year": "", "pdf": ["https://pdfs.semanticscholar.org/5eef/e98aafffe665b19de515e3ba90c9c0b7219c.pdf"], "doi": []}, {"id": "620339aef06aed07a78f9ed1a057a25433faa58b", "title": "Human Action Recognition and Prediction: A Survey", "year": "2018", "pdf": ["https://arxiv.org/pdf/1806.11230.pdf"], "doi": []}, {"id": "878f70f6abb83f5158ca0bacfc2bacd49b1886b1", "title": "Aligning Artificial Neural Networks to the Brain Yields Shallow Recurrent Architec- Tures", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/878f/70f6abb83f5158ca0bacfc2bacd49b1886b1.pdf"], "doi": []}, {"id": "5a77877689e44e3ed48250f53e05b0d37bd901d7", "title": "Morph: Flexible Acceleration for 3D CNN-Based Video Understanding", "year": "2018", "pdf": [], "doi": ["http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8574597"]}, {"id": "d3f5a1848b0028d8ab51d0b0673732cad2e3c8c9", "title": "STAIR Actions: A Video Dataset of Everyday Home Actions", "year": "2018", "pdf": ["https://arxiv.org/pdf/1804.04326.pdf"], "doi": []}, {"id": "54c7c3909c7e1e827befdbe8d2595a3b196ba1b8", "title": "AVA: A Video Dataset of Spatio-Temporally Localized Atomic Visual Actions", "year": "2018", "pdf": [], "doi": ["http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8578731"]}, {"id": "593045f63de1273d116097eeea6fda7aa244e74d", "title": "Qiniu Submission to ActivityNet Challenge 2018", "year": "2018", "pdf": ["https://arxiv.org/pdf/1806.04391.pdf"], "doi": []}, {"id": "5b002afc3fda9ee321babab4db857c819ec5c46d", "title": "Repair Genetic Disease in Embryo", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/5b00/2afc3fda9ee321babab4db857c819ec5c46d.pdf"], "doi": []}, {"id": "a1eddece7741f0c4199989bb08326ef36b752a53", "title": "Objects Levitating with Light", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/a1ed/dece7741f0c4199989bb08326ef36b752a53.pdf"], "doi": []}, {"id": "85f957b5eaf9e2145e4271ebb05368e73d5b0d68", "title": "Muon Detector Measure Electric Potential", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/85f9/57b5eaf9e2145e4271ebb05368e73d5b0d68.pdf"], "doi": []}, {"id": "058b215d87670381ee32035b69fcc9cddda59a47", "title": "Recovering Scattered Data with SMART", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/058b/215d87670381ee32035b69fcc9cddda59a47.pdf"], "doi": []}, {"id": "362341d17940d085c983f541f1fe12b633a5ed9f", "title": "Netflix Speed Up Biological Imaging", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/3623/41d17940d085c983f541f1fe12b633a5ed9f.pdf"], "doi": []}, {"id": "5206112dbd86d62cdcd7029a7116173990428040", "title": "Next Generation Optical Tweezers", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/5206/112dbd86d62cdcd7029a7116173990428040.pdf"], "doi": []}, {"id": "bdd2ba9e8b368638c5ddb9f3070275342c14ec31", "title": "Chip Up AI Performance", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/bdd2/ba9e8b368638c5ddb9f3070275342c14ec31.pdf"], "doi": []}, {"id": "4c605da6dc4a0f487286cd4cc2c58289c862b447", "title": "Planets Discovered Using AI", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/4c60/5da6dc4a0f487286cd4cc2c58289c862b447.pdf"], "doi": []}, {"id": "8f35e4b29c77c1ddae1f315a0bba43a6f0d0a433", "title": "Artificial Intelligence Accelerates Discovery", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/8f35/e4b29c77c1ddae1f315a0bba43a6f0d0a433.pdf"], "doi": []}, {"id": "931334796221e5420c2413e35ecec69bc59a6d15", "title": "Artificial Intelligence Bring Sun Power to Earth", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/9313/34796221e5420c2413e35ecec69bc59a6d15.pdf"], "doi": []}, {"id": "c82c059e23eb9e92c814d1ac5025f5f720479679", "title": "Machine Learning Quantum Advantage", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/c82c/059e23eb9e92c814d1ac5025f5f720479679.pdf"], "doi": []}, {"id": "0e4a4f9874d4c37caa6fa63247c7e02fe160312e", "title": "Machine Learning Quantum Fireworks", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/0e4a/4f9874d4c37caa6fa63247c7e02fe160312e.pdf"], "doi": []}, {"id": "cb0e0f18e5be5c7f9307fd523d8eb680aa0fcc2a", "title": "Nanosponges for Rheumatoid Arthritis", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/cb0e/0f18e5be5c7f9307fd523d8eb680aa0fcc2a.pdf"], "doi": []}, {"id": "7e970550d48080d6ac988e069bd6c3ed5b95c325", "title": "Proteins Associated with Cancer", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/7e97/0550d48080d6ac988e069bd6c3ed5b95c325.pdf"], "doi": []}, {"id": "9091376ea8cf4d9d28c8ebaecf554ad515e0ea50", "title": "Deep Learning Human Activities", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/9091/376ea8cf4d9d28c8ebaecf554ad515e0ea50.pdf"], "doi": []}, {"id": "aa32bb2719d64d41545bf9ac9fe259833bcb14e3", "title": "Image Analysis with Deep Learning", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/aa32/bb2719d64d41545bf9ac9fe259833bcb14e3.pdf"], "doi": []}, {"id": "0aba7929b9d019bc8e1bb37827cda170a10e8d4f", "title": "Machine Learning Quantum Phases", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/0aba/7929b9d019bc8e1bb37827cda170a10e8d4f.pdf"], "doi": []}, {"id": "253fa8280c2898fcdedaca7122e749cb3e1d4b57", "title": "AI Needs Hardware Accelerators", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/253f/a8280c2898fcdedaca7122e749cb3e1d4b57.pdf"], "doi": []}, {"id": "f1c357d9543b0dc607d4222701c64deffcabc6ab", "title": "Machine Learning World ' s Oceans", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/f1c3/57d9543b0dc607d4222701c64deffcabc6ab.pdf"], "doi": []}, {"id": "02e40be81c453ea80e5e14d4a76136a804c7c90d", "title": "Faster and Simpler Deep Learning", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/02e4/0be81c453ea80e5e14d4a76136a804c7c90d.pdf"], "doi": []}, {"id": "0be47c361a25cdf188639e99b695b535f9cc662f", "title": "Nano-Electrode Detect Early Cancer", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/0be4/7c361a25cdf188639e99b695b535f9cc662f.pdf"], "doi": []}, {"id": "3e8fc0da19772f2d46af0e6d84c59d6b66be72f2", "title": "Memristor Speeding Up AI", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/3e8f/c0da19772f2d46af0e6d84c59d6b66be72f2.pdf"], "doi": []}, {"id": "ceac97bd0b90f1bacd7e43d67cb589ef5abe3e5f", "title": "Machine Learning Quantum Sensing", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/ceac/97bd0b90f1bacd7e43d67cb589ef5abe3e5f.pdf"], "doi": []}, {"id": "223afe4fad76fcec6e4f6d90b4bc2b9f45da6f4b", "title": "Cancer Reporting Machine Learning", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/223a/fe4fad76fcec6e4f6d90b4bc2b9f45da6f4b.pdf"], "doi": []}, {"id": "ba8c1fdd268c35a2d7a1fd60a101fd026f793f3e", "title": "AI Exploration of Underwater Habitats", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/ba8c/1fdd268c35a2d7a1fd60a101fd026f793f3e.pdf"], "doi": []}, {"id": "cc749cf9f26fcf07a7bde6e54f78e0592d2fd802", "title": "Deep Learning Smartphone Microscope", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/cc74/9cf9f26fcf07a7bde6e54f78e0592d2fd802.pdf"], "doi": []}, {"id": "fba86c9e8200c18ca788a4d5962853bda954bb71", "title": "Syndromes Data Mining", "year": "2019", "pdf": ["https://pdfs.semanticscholar.org/fba8/6c9e8200c18ca788a4d5962853bda954bb71.pdf"], "doi": []}, {"id": "5a29df900d1a96d4b73daa6df36b762b5f652152", "title": "AI Meets Your Shopping Experience", "year": "2018", "pdf": ["https://pdfs.semanticscholar.org/5a29/df900d1a96d4b73daa6df36b762b5f652152.pdf"], "doi": []}]}
\ No newline at end of file |