Explore the latest peer-reviewed research with AI-generated summaries, key findings, and insights for easy understanding. All content is legally sourced from academic metadata with links to original papers.
SUMMARY: Self-supervised deep language modeling has shown unprecedented success across natural language tasks, and has recently been repurposed to biological sequences. AVAILABILITY AND IMPLEMENTATION...
Classification systems differ vastly in terms of the nature and origin of their knowledge about image variations. Yuille, for example, represented eyes by a circle within an almond-shape and defined a...
Signal peptides (SPs) are short amino acid sequences that control protein secretion and translocation in all living organisms. SPs can be predicted from sequence data, but existing algorithms are unab...
Fully Convolutional Neural Networks (FCNNs) with contracting and expanding paths have shown prominence for the majority of medical image segmentation applications since the past decade. We have valida...
Object detection techniques are the foundation for the artificial intelligence field. The central insight is the YOLO algorithm improvement is still ongoing.This article briefly describes the developm...
This research explores ByteTrack: Multi-object Tracking by Associating Every Detect..., contributing new insights to the field of Artificial Intelligence.
This research explores Swin UNETR: Swin Transformers for Semantic Segmentation of B..., contributing new insights to the field of Artificial Intelligence.
We present SR3, an approach to image Super-Resolution via Repeated Refinement. We evaluate SR3 on a 4× super-resolution task on ImageNet, where SR3 outperforms baselines in human evaluation and classi...
Working with large amounts of text data has become hectic and time-consuming. That said, we propose an approach that relies on Question Answering for acquiring information from unstructured data, in o...
Particle swarm optimization (PSO) is one of the most well-regarded swarm-based algorithms in the literature. Moreover, this paper reviews recent studies that utilize PSO to solve feature selection pro...
This research explores BEVFormer: Learning Bird’s-Eye-View Representation from Mult..., contributing new insights to the field of Artificial Intelligence.
Ensemble learning techniques have achieved advanced performance in diverse machine learning applications by combining the predictions from two or more base models. The study focuses on the widely used...
This research explores Simple Baselines for Image Restoration, contributing new insights to the field of Artificial Intelligence.
This research explores TensoRF: Tensorial Radiance Fields, contributing new insights to the field of Artificial Intelligence.
Generalization to out-of-distribution (OOD) data is a capability natural to humans yet challenging for machines to reproduce. Then, we conduct a thorough review into existing methods and theories.
Modern image inpainting systems, despite the significant progress, often struggle with large missing areas, complex geometric structures, and high-resolution images. Our model generalizes surprisingly...
This research explores Image fusion in the loop of high-level vision tasks: A seman..., contributing new insights to the field of Artificial Intelligence.
In general, the goal of existing infrared and visible image fusion (IVIF) methods is to make the fused image contain both the high-contrast regions of the infrared image and the texture details of the...
In this paper, we propose a new comprehensive realistic cyber security dataset of IoT and IIoT applications, called Edge-IIoTset, which can be used by machine learning-based intrusion detection system...
Following the current interest in developing automatic question answering systems, we analyse alternative approaches for finding suitable answers from a list of Frequently Asked Questions (FAQs), in P...