Image Classification

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Smart Ternary Quantization

ICLR 2020

Low bit quantization such as binary and ternary quantization is a common approach to alleviate this resource requirements.

IMAGE CLASSIFICATION QUANTIZATION

Meta-Learning Initializations for Image Segmentation

ICLR 2020

While meta-learning approaches that utilize neural network representations have made progress in few-shot image classification, reinforcement learning, and, more recently, image semantic segmentation, the training algorithms and model architectures have become increasingly specialized to the few-shot domain.

FEW-SHOT IMAGE CLASSIFICATION FEW-SHOT LEARNING SEMANTIC SEGMENTATION

Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation

ICLR 2020

We propose a hybrid training methodology: 1) take a converted SNN and use its weights and thresholds as an initialization step for spike-based backpropagation, and 2) perform incremental spike-timing dependent backpropagation (STDB) on this carefully initialized network to obtain an SNN that converges within few epochs and requires fewer time-steps for input processing.

IMAGE CLASSIFICATION

WHAT DATA IS USEFUL FOR MY DATA: TRANSFER LEARNING WITH A MIXTURE OF SELF-SUPERVISED EXPERTS

ICLR 2020

We assume that a client, a target application with its own small labeled dataset, is only interested in fetching a subset of the server’s data that is most relevant to its own target domain.

IMAGE CLASSIFICATION INSTANCE SEGMENTATION OBJECT DETECTION SEMANTIC SEGMENTATION TRANSFER LEARNING

Improving the Gating Mechanism of Recurrent Neural Networks

ICLR 2020

In this work, we revisit the gating mechanisms widely used in various recurrent and feedforward networks such as LSTMs, GRUs, or highway networks.

LANGUAGE MODELLING SEQUENTIAL IMAGE CLASSIFICATION

Tree-structured Attention Module for Image Classification

ICLR 2020

Our module allows a model to achieve higher performance in a highly parameter-efficient manner.

IMAGE CLASSIFICATION

Laconic Image Classification: Human vs. Machine Performance

ICLR 2020

Given a classifier and a test image, we compute an approximate minimal-entropy positive image for which the classifier provides a correct classification, becoming incorrect upon any further reduction.

IMAGE CLASSIFICATION

Scale-Equivariant Steerable Networks

ICLR 2020

The effectiveness of Convolutional Neural Networks (CNNs) has been substantially attributed to their built-in property of translation equivariance.

IMAGE CLASSIFICATION

Unrestricted Adversarial Examples via Semantic Manipulation

ICLR 2020

Machine learning models, especially deep neural networks (DNNs), have been shown to be vulnerable against \emph{adversarial examples} which are carefully crafted samples with a small magnitude of the perturbation.

IMAGE CAPTIONING IMAGE CLASSIFICATION