In recent years, deep learning (DL), a re-branding of neural networks (NNs), has risen to the top in numerous areas, namely computer vision (CV), speech recognition, natural language processing, etc. Whereas remote sensing (RS) possesses number unique challenges, primarily related sensors and applications, inevitably RS draws from many same theories as CV; e.g., statistics, fusion, machine learning, name few. This means that community should be aware of, if not at leading edge advancements...

An accurate and robust perception system is key to understanding the driving environment of autonomous robots. Autonomous needs 3-D information about objects, including object’s location pose, understand clearly. A camera sensor widely used in because its richness color texture, low price. The major problem with lack information, which necessary environment. In addition, scale change occlusion make object detection more challenging. Many deep learning-based methods, such as depth estimation,...

Wearables are a multi-billion-dollar business with more growth expected. Wearable technology is fully entrenched at multiple levels of athletic competition, especially the National Collegiate Athletic Association (NCAA) and professional where these solutions used to gain competitive advantages by assessing health performance elite athletes. However, through Science Foundation (NSF) Innovation Corps (I-Corps) training experience, different story emerged based on pilot interviews from coaches...

Collision avoidance is a critical task in many applications, such as ADAS (advanced driver-assistance systems), industrial automation and robotics. In an setting, certain areas should be off limits to automated vehicle for protection of people high-valued assets. These can quarantined by mapping (e.g., GPS) or via beacons that delineate no-entry area. We propose delineation method where the utilizes LiDAR (Light Detection Ranging) single color camera detect passive model-predictive control...

Opportunities to apply data mining techniques analyze educational and improve learning are increasing. A multitude of being produced by institutional technology, e-learning resources, online virtual courses. These could be used educators understand the behaviors students. The obtained raw that must analyzed, requiring predict useful information about students, such as academic performance, among other things. Many researchers have traditional machine performance very little research has been...

Fish species recognition is crucial to identifying the abundance of fish in a specific area, controlling production management, and monitoring ecosystem, especially endangered species, which makes accurate essential. In this work, problem formulated as an object detection model handle multiple single image, challenging classify using simple classification network. The proposed consists MobileNetv3-large VGG16 backbone networks SSD head. Moreover, class-aware loss function solve class...

The pursuit of autonomous driving relies on developing perception systems capable making accurate, robust, and rapid decisions to interpret the environment effectively. Object detection is crucial for understanding at these systems’ core. While 2D object classification have advanced significantly with advent deep learning (DL) in computer vision (CV) applications, they fall short providing essential depth information, a key element comprehending environments. Consequently, 3D becomes...

Since the state-of-the-art deep learning algorithms demand a large training dataset, which is often unavailable in some domains, transfer of knowledge from one domain to another has been trending technique computer vision field. However, this method may not be straight-forward task considering several issues such as original network size or differences between source and target domain. In paper, we perform for semantic segmentation off-road driving environments using pre-trained called...

Background: Inertial Measurement Unit (IMU) based wearables have been the focus of many recent sports medicine research efforts. Objective: The goal this narrative-driven literature review is to provide current state IMU-based wearable technology in Sports Medicine for benefit practitioners and athletic trainers. Method: A search was performed using university library resources; specifically, PubMed, EBSCO Discovery Google Scholar engines were used identify appropriate peer-reviewed studies...

Human activity recognition plays a crucial role in Advanced Driver-Assisted Systems (ADAS). A significant challenge achieving automotive autonomy lies the difficulty faced by self-driving cars navigating roads without operational traffic lights. In such scenarios, human intervention often involves directing vehicles through signaling with appropriate signs or gestures. This poses considerable for autonomous to interpret these gestures effectively. study focuses on leveraging dataset of...

In the context of autonomous driving, existing semantic segmentation concept strongly supports on-road driving where hard inter-class boundaries are enforced and objects can be categorized based on their visible structures with high confidence. Due to well-structured nature typical scenes, current road extraction processes largely successful most types vehicles able traverse through area that is detected as road. However, off-road domain has many additional uncertainties such uneven terrain...

Three-dimensional object detection is crucial for autonomous driving to understand the environment. Since pooling operation causes information loss in standard CNN, we designed a wavelet-multiresolution-analysis-based 3D network without operation. Additionally, instead of using single filter like convolution, used lower-frequency and higher-frequency coefficients as filter. These filters capture more relevant parts than filter, enlarging receptive field. The model comprises discrete wavelet...

In video-based fish surveys, species recognition plays a vital role in stock assessments, ecosystem analysis, production management, and protection of endangered species. However, implementing detection algorithms underwater environments presents significant challenges due to factors such as varying lighting conditions, water turbidity, the diverse appearances this work, transformer-enhanced YOLOv8 (YOLOv8-TF) is proposed for recognition. The YOLOv8-TF enhances performance by adjusting depth...

<div class="section abstract"><div class="htmlview paragraph">The application of multi-sensor fusion for enhanced distance estimation accuracy in dynamic environments is crucial advanced driver assistance systems (ADAS) and autonomous vehicles. The Limitations single sensors such as cameras or radar adverse conditions motivate the use combined camera data to improve reliability, adaptability, object recognition. A approach using an Extended Kalman Filter (EKF) proposed combine...

We present a mammographic computer aided diagnosis (CAD) system, which uses an adaptive level set segmentation method (ALSSM), segments suspicious masses in the polar domain and adaptively adjusts border threshold at each angle to provide high-quality results. The primary contribution of this paper is speed function for controlling segmentation. To assess efficacy 60 relatively difficult cases (30 benign, 30 malignant) from Digital Database Screening Mammography (DDSM) are analyzed. analyzed...

Motion planning of an autonomous mobile robot is involved in generating safe, optimal, short, and/or reasonable trajectories its workspace and finally reaching final target while avoiding collision with obstacles escaping traps. This paper presents a new hybrid model to optimize trajectory the global path using graph-based search algorithm associated ant colony optimization (ACO) method. Once graph representing populated modelled by MAKLINK theory, Dijkstra utilized seek sub-optimal...