Computer vision technologies have attracted significant interest in precision agriculture in
recent years. At the core of robotics and artificial intelligence, computer vision enables …

Analyzing short texts infers discriminative and coherent latent topics that is a critical and
fundamental task since many real-world applications require semantic understanding of …

State-of-the-art computer vision systems are trained to predict a fixed set of predetermined
object categories. This restricted form of supervision limits their generality and usability since …

Analogue in-memory computing (AIMC) with resistive memory devices could reduce the
latency and energy consumption of deep neural network inference tasks by directly …

We have now entered the era of trillion parameter machine learning models trained on
billion-sized datasets scraped from the internet. The rise of these gargantuan datasets has …

Automatically describing the content of an image is a fundamental problem in artificial
intelligence that connects computer vision and natural language processing. In this paper …

Automatically describing an image with a sentence is a long-standing challenge in computer
vision and natural language processing. Due to recent progress in object detection, attribute …

There is considerable interest in the task of automatically generating image captions.
However, evaluation is challenging. Existing automatic evaluation metrics are primarily …

The Flickr30k dataset has become a standard benchmark for sentence-based image
description. This paper presents Flickr30k Entities, which augments the 158k captions from …

We present a new dataset with the goal of advancing the state-of-the-art in object
recognition by placing the question of object recognition in the context of the broader …