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Debdoot Sheet
Researcher at Indian Institute of Technology Kharagpur
Publications - 129
Citations - 2813
Debdoot Sheet is an academic researcher from Indian Institute of Technology Kharagpur. The author has contributed to research in topics: Convolutional neural network & Segmentation. The author has an hindex of 19, co-authored 121 publications receiving 1824 citations. Previous affiliations of Debdoot Sheet include Jadavpur University & Ludwig Maximilian University of Munich.
Papers
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Proceedings ArticleDOI
Comparative evaluation of speckle reduction algorithms in optical coherence tomography
TL;DR: In this article, a comparative evaluation of six speckle reduction filtering techniques based on local statistics, median filtering, pixel homogeneity, geometric filtering, and transformed domain homomorphic filtering is presented.
Posted Content
A Two-Stage Multiple Instance Learning Framework for the Detection of Breast Cancer in Mammograms
Sarath Chandra K,Arunava Chakravarty,Nirmalya Ghosh,Tandra Sarkar,Ramanathan Sethuraman,Debdoot Sheet +5 more
TL;DR: In this article, a two-stage Multiple Instance Learning (MIL) framework was used for image-level detection of malignancy in mammograms, which is a challenging task given the small size of the mass regions and difficulty in discriminating between malignant, benign and healthy dense fibro-glandular tissue.
Posted Content
IROS 2019 Lifelong Robotic Vision Challenge -- Lifelong Object Recognition Report
Qi She,Fan Feng,Qi Liu,Rosa H. M. Chan,Xinyue Hao,Chuanlin Lan,Qihan Yang,Vincenzo Lomonaco,German Ignacio Parisi,Heechul Bae,Eoin Brophy,Baoquan Chen,Gabriele Graffieti,Vidit Goel,Hyonyoung Han,Sathursan Kanagarajah,Somesh Kumar,Siew-Kei Lam,Tin Lun Lam,Liang Ma,Davide Maltoni,Lorenzo Pellegrini,Duvindu Piyasena,Shiliang Pu,Debdoot Sheet,Soonyong Song,Young-Sung Son,Zhengwei Wang,Tomas E. Ward,Jianwen Wu,Meiqing Wu,Di Xie,Yangsheng Xu,Lin Yang,Qiaoyong Zhong,Liguang Zhou +35 more
TL;DR: This report summarizes IROS 2019-Lifetime Robotic Vision Competition (Lifelong Object Recognition Challenge) with methods and results from the top $8$ finalists (out of over~$150$ teams).
Journal ArticleDOI
Local instance and context dictionary-based detection and localization of abnormalities
Abstract: Studies on contextual abnormality detection and localization for images and videos are presented in this work. The task of detecting abnormalities becomes challenging while considering the context in the scene. Some object which is normal in one scenario may be considered as abnormal in another. We present conceptually simple, flexible and a general framework, by incorporating instance segmentation, skip-gram with negative sampling and isolation forest for detecting and localizing contextual abnormality in images and videos. The skip-gram-based model is generally used for word2vec in natural language processing for finding the similarity between words. In this work, we extended them to detect the object-based abnormality in the images and video. Then we introduce the voting technique, which overcomes the variable-length feature vector issues; the decision of normal or abnormal object is based on this technique by considering the output from the isolation forest. We consider the anomalous events as scenarios having a different distribution from the normal settings such as a less frequently seen object in a given combination, the increase in the number of specific objects category, the object’s presence at unseen distance and occupancy of the out-of-vocabulary object. We observed that the proposed framework works in the proximity of multiple object categories and camera motion in the natural capture videos.
Journal ArticleDOI
CholecTriplet2022: Show me a tool and tell me the triplet - an endoscopic vision challenge for surgical action triplet detection
Saurav Sharma,Deepak Alapatt,Kun Yuan,Wolfgang Reiter,Amine Yamlahi,Guoyan Zheng,Helena R. Torres,Satoshi Kondo,Felix Holm,Shuangchun Gui,Sista Raviteja,Rachana Sathish,B N Bhattarai,Guo Rui,Melanie Schellenberg,Zhenkun Wang,Shrawan Kumar Thapa,Thuy Nuong Tran,Jaime C. Fonseca,Pietro Mascagni,Chinedu Innocent Nwoye,Tong Yu,Aditya Murali,Armine Vardazaryan,Jonas Hajek,Finn-Henri Smidt,Xiaoyang Zou,Bruno Oliveira,Satoshi Kasai,Ege Özsoy,Han Li,Pranav Poudel,Ziheng Wang,Joao L. Vilacca,Tobias Czempiel,Debdoot Sheet,Max Berniker,Patrick Godau,Pedro Morais,S. Regmi,Jan-Hinrich Nolke,Estevão Lima,Eduard Vazquez,Lena Maier-Hein,Nassir Navab,Barbara Seeliger,Cristians Gonzalez,Didier Mutter,Nicolas Padoy +48 more
TL;DR: The CholecTriplet2022 challenge as discussed by the authors extended surgical action triplet modeling from recognition to detection, which includes weakly-supervised bounding box localization of every visible surgical instrument (or tool), as the key actors, and modeling of each tool-activity in the form of triplet.