Multiple Instance Learning: A Survey of Problem Characteristics and
Applications

Multiple Instance Learning: A Survey of Problem Characteristics and Applications

11 December 2016

Papers citing "Multiple Instance Learning: A Survey of Problem Characteristics and Applications"

19 / 69 papers shown

Title
Multiple instance learning on deep features for weakly supervised object detection with extreme domain shifts Nicolas Gonthier Saïd Ladjal Y. Gousseau WSOD 29 28 0 03 Aug 2020
MINI-Net: Multiple Instance Ranking Network for Video Highlight Detection Fa-Ting Hong Xuanteng Huang Weihong Li Weishi Zheng 10 61 0 20 Jul 2020
Modern Hopfield Networks and Attention for Immune Repertoire Classification Michael Widrich Bernhard Schafl Hubert Ramsauer Milena Pavlović Lukas Gruber ... Johannes Brandstetter G. K. Sandve Victor Greiff Sepp Hochreiter Günter Klambauer 193 117 0 16 Jul 2020
Hopfield Networks is All You Need Hubert Ramsauer Bernhard Schafl Johannes Lehner Philipp Seidl Michael Widrich ... David P. Kreil Michael K Kopp Günter Klambauer Johannes Brandstetter Sepp Hochreiter 24 415 0 16 Jul 2020
Revisiting Data Complexity Metrics Based on Morphology for Overlap and Imbalance: Snapshot, New Overlap Number of Balls Metrics and Singular Problems Prospect José Daniel Pascual-Triana D. Charte Marta Andrés Arroyo Alberto Fernández Francisco Herrera 6 18 0 15 Jul 2020
Attentive Weakly Supervised land cover mapping for object-based satellite image time series data with spatial interpretation Dino Ienco Y. J. E. Gbodjo R. Interdonato R. Gaetano 29 2 0 30 Apr 2020
Representation Learning of Histopathology Images using Graph Neural Networks Mohammed Adnan Shivam Kalra Hamid R. Tizhoosh OOD 21 98 0 16 Apr 2020
Weakly-Supervised Action Localization with Expectation-Maximization Multi-Instance Learning Zhekun Luo Devin Guillory Baifeng Shi Wei Ke Fang Wan Trevor Darrell Huijuan Xu 13 119 0 31 Mar 2020
See and Read: Detecting Depression Symptoms in Higher Education Students Using Multimodal Social Media Data Paulo Mann A. Paes Elton H. Matsushima 16 40 0 03 Dec 2019
Deep Weakly-Supervised Domain Adaptation for Pain Localization in Videos R Gnana Praveen Eric Granger P. Cardinal 41 25 0 17 Oct 2019
Anomaly Detection with Inexact Labels Tomoharu Iwata Machiko Toyoda Shotaro Tora N. Ueda 19 14 0 11 Sep 2019
Deep Weakly-Supervised Learning Methods for Classification and Localization in Histology Images: A Survey Jérôme Rony Soufiane Belharbi Jose Dolz Ismail Ben Ayed Luke McCaffrey Eric Granger 27 70 0 08 Sep 2019
Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action Classifier for Anomaly Detection Jia-Xing Zhong Nannan Li Weijie Kong Shan Liu Thomas H. Li Ge Li NoLa SSL 24 397 0 18 Mar 2019
Multi Instance Learning For Unbalanced Data Mark Kozdoba E. Moroshko Lior Shani Takuya Takagi Takashi Katoh Shie Mannor K. Crammer 16 1 0 17 Dec 2018
Weakly Supervised Object Detection in Artworks Nicolas Gonthier Y. Gousseau Saïd Ladjal Olivier Bonfait ObjD 17 70 0 05 Oct 2018
Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis V. Cheplygina Marleen de Bruijne J. Pluim 16 745 0 17 Apr 2018
Attention-based Deep Multiple Instance Learning Maximilian Ilse Jakub M. Tomczak Max Welling 84 1,759 0 13 Feb 2018
Bag-Level Aggregation for Multiple Instance Active Learning in Instance Classification Problems M. Carbonneau Eric Granger G. Gagnon 9 31 0 06 Oct 2017
Using Neural Network Formalism to Solve Multiple-Instance Problems Tomás Pevný P. Somol 24 27 0 23 Sep 2016