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10/19/2022
Attaining Class-level Forgetting in Pretrained Model using Few Samples
In order to address real-world problems, deep learning models are jointl...
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12/23/2021
DILF-EN framework for Class-Incremental Learning
Deep learning models suffer from catastrophic forgetting of the classes ...
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06/30/2021
Fair Visual Recognition in Limited Data Regime using Self-Supervision and Self-Distillation
Deep learning models generally learn the biases present in the training ...
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03/30/2021
Rectification-based Knowledge Retention for Continual Learning
Deep learning models suffer from catastrophic forgetting when trained in...
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03/01/2021
Few-Shot Lifelong Learning
Many real-world classification problems often have classes with very few...
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11/22/2020
RNNP: A Robust Few-Shot Learning Approach
Learning from a few examples is an important practical aspect of trainin...
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06/29/2020
Improving Few-Shot Learning using Composite Rotation based Auxiliary Task
In this paper, we propose an approach to improve few-shot classification...
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06/08/2020
Passive Batch Injection Training Technique: Boosting Network Performance by Injecting Mini-Batches from a different Data Distribution
This work presents a novel training technique for deep neural networks t...
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05/27/2020
AVGZSLNet: Audio-Visual Generalized Zero-Shot Learning by Reconstructing Label Features from Multi-Modal Embeddings
In this paper, we solve for the problem of generalized zero-shot learnin...
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10/21/2019
CPWC: Contextual Point Wise Convolution for Object Recognition
Convolutional layers are a major driving force behind the successes of d...
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03/11/2019