Underwater small objects detection based on self-attention and improved pyramid network
Addressing the challenges of limited feature information and decreased detection accuracy in underwater small object detection tasks due to underwater environmental effects, we propose an underwater small object detection algorithm SF-Bi-YOLOv8 based on ...
DU Ruishan +3 more
doaj +1 more source
Emergent auditory feature tuning in a real-time neuromorphic VLSI system [PDF]
Many sounds of ecological importance, such as communication calls, are characterized by time-varying spectra. However, most neuromorphic auditory models to date have focused on distinguishing mainly static patterns, under the assumption that dynamic ...
Martin eCoath +25 more
core +1 more source
An Efficient Bidirectional Point Pyramid Attention Network for 3D Point Cloud Completion
Point cloud completion is a necessary task in real-world applications of recovering a complete geometry from missing regions of 3D objects. Furthermore, model efficiency is of vital importance in computer vision.
Yang Li +3 more
core +1 more source
Emerging Materials and Future Strategies for Solid Oxide Electrochemical Cells
Solid oxide electrochemical cells operate under strongly coupled electrochemical and thermodynamic conditions, where performance is constrained by interactions among crystal structure, defect chemistry, and interfacial evolution. This review, based on a structure‐defect‐property‐durability framework, reveals the roles of lattice symmetry and defect ...
Qiuchun Lu +4 more
wiley +1 more source
Bidirectional branch and bound for controlled variable selection. Part II: exact local method for self-optimizing control [PDF]
The selection of controlled variables (CVs) from available measurements through enumeration of all possible alternatives is computationally forbidding for large-dimensional problems. In Part I of this work [Cao, Y., & Kariwala, V.
Vinay Cao +5 more
core +1 more source
Object Detection Using Improved Bi-Directional Feature Pyramid Network
Conventional single-stage object detectors have been able to efficiently detect objects of various sizes using a feature pyramid network. However, because they adopt a too simple manner of aggregating feature maps, they cannot avoid performance ...
Byung Cheol Song +2 more
core +1 more source
Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source
In complex coal mine environment and poor lighting conditions, the existing target detection technology is difficult to meet the needs of intelligent inspection.
Junfei TANG +5 more
doaj +1 more source
An Enhanced Feature Pyramid Object Detection Network for Autonomous Driving
Feature Pyramid Network (FPN) builds a high-level semantic feature pyramid and detects objects of different scales in corresponding pyramid levels. Usually, features within the same pyramid levels have the same weight for subsequent object detection ...
Shuwei Zhang +3 more
core +1 more source
Volumetric texture segmentation by discriminant feature selection and multiresolution classification [PDF]
In this paper, a multiresolution volumetric texture segmentation (M-VTS) algorithm is presented. The method extracts textural measurements from the Fourier domain of the data via subband filtering using an orientation pyramid (Wilson and Spann, 1988).
Constantino C Reyes Aldasoro (16060949) +7 more
core +1 more source

