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...

NASA's Cyclone Global Navigation Satellite System (CYGNSS) mission has gained significant attention within the land remote sensing community for estimating soil moisture (SM) by using Reflectometry (GNSS-R) technique. CYGNSS constellation generates Delay-Doppler Maps (DDM)s, containing important earth surface information from GNSS reflection measurements. Many previous studies considered only designed features DDM such as peak value of DDM, whereas whole image is affected SM,...

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...

Species recognition is an important aspect of video based surveys, which support stock assessments, inspecting the ecosystem, handling production management, and protecting endangered species. It a challenging task to implement fish species detection algorithms in underwater environments. In this work, we introduce YOLOv5 model for that can be implemented as object analyzing multiple fishes single image. Moreover, have modified depth scale different layers backbone obtain improved results on...

Fish species recognition and detection are essential for fishery industries. Accurate robust classification play a vital role in monitoring fish activities identifying the distribution of specific species, which is to know endangered species. It also controlling production overall ecosystem control management. However, current artificial intelligence technologies, such as deep learning, limited ocean system compared other areas like robotics security. The major challenge building learning...

A high spatial and temporal resolution global soil moisture product is essential for understanding hydrologic meteorological processes enhancing agricultural applications. Global Navigation Satellite System (GNSS) signals at L-band frequencies that reflect off the land surface can convey high-resolution information, including (SM). Cyclone (CYGNSS) constellation generates Delay-Doppler Maps (DDMs) contain important Earth information from GNSS reflection measurements. DDMs are affected by...

Video surveys are commonly used to monitor the abundance and distribution of managed species support management. However, considerable effort, time, cost required for human review automated fish recognition provides an effective solution remove bottleneck post-processing. Implementing detection techniques underwater imagery is a challenging task. In this work, we present Multiple Instance Active-learning Fish-species Recognition (MI-AFR), which formulated as object detection-based approach...

AbstractExamining fabric weave patterns (FWPs) is connected to image-based surface texture feature (STF) acquisition, which can be difficult due the structural complexity of woven fabrics. Randomly capturing static images may not correlate with entire STF a fabric. Traditionally, FWPs analysis conducted by human vision, causes an intensive cognitive load. Ultimately, vision-based load leads ineffective quality inspection and error-prone results. Given above challenges, this study proposes...

Accurate fish species identification is essential for stock assessments, production management, document ecosystem changes, and protection of endangered species. Image processing computer vision techniques have been widely employed detection, classification, tracking, reducing human efforts in these tasks. However, methods often rely on extensive training data with correct annotations. Annotating many images captured from marine environments poses a significant challenge. This work proposes...

Identification of fish species is vital for fisheries management, stock assessments, protection endangered species, and ecosystem management. Image based surveys often deploy video cameras that are used to collect large image datasets reviewed by a human observer identify generate numerical count at each station. One main challenge in labeling or annotating such dataset it requires huge amount time, cost, effort. Recently, general adversarial network (GAN) generative techniques have drawn...

Fish species must be identified for stock assessments, ecosystem monitoring, production management, and the conservation of endangered species. Implementing algorithms fish detection in underwater settings like Gulf Mexico poses a formidable challenge. Active learning, method that efficiently identifies informative samples annotation while staying within budget, has demonstrated its effectiveness context object recent times. In this study, we present an active model designed recognition...

Adaptive cruise control (ACC), a common feature in an autonomous vehicle, is intended to automatically adjust the vehicle speed and maintain safe distance from its preceding avoid collision. The main challenge filter sensor data accurately, system can make decision quickly. This paper proposed method for ACC using Extended Kalman (EKF) Proportional Integral Derivative (PID) controller, which estimate acceleration or braking of by adjusting following vehicle. assessed under various PID...

For autonomous driving, pedestrian and road signs detection are key elements. There is much existing literature available addressing this issue successfully. However, the system requires a large diverse set of training samples labeling in real-world environments. Manual annotation these somewhat challenging time-consuming. In paper, our goal to get better accuracy with minimal data. this, we have employed active learning algorithm. Active useful method that selects only effective portion...

Baited underwater video sampling is a common method to monitor fish populations, yet the data requirements associated with imagery leads bottlenecks in productivity. Image analysis that incorporates automated methods through deep-learning models could provide solutions. These have potential improve efficiency, and decrease cost of producing information on populations habitats. In order reduce human intervention, these must produce precise, accurate results. While for gauging model...

NASA Cyclone Global Navigation Satellite System (CYGNSS) mission has gained attention within the land remote sensing community for estimating soil moisture (SM) by using Reflectometry (GNSS-R) technique. CYGNSS constellation generates Delay-Doppler Maps (DDM) that contain valuable earth surface information from GNSS reflection measurements. Existing approaches use predefined features DDMs to estimate SM. This pa-per presents a deep-learning framework learn optimal The proposed approach is...

Accurate recognition of multiple fish species is essential in marine ecology and fisheries. Precisely classifying tracking these enriches our comprehension their movement patterns empowers us to create precise maps species-specific territories. Such profound insights are pivotal conserving endangered species, promoting sustainable fishing practices, preserving ecosystems' overall health equilibrium. To partially address needs, we present a proposed model that combines YOLOv8 for object...

The deep neural network has found widespread application in object detection due to its high accuracy. However, performance typically depends on the availability of a substantial volume accurately labeled data. Several active learning approaches have been proposed reduce labeling dependency based confidence detector. Nevertheless, these tend exhibit biases toward high-performing classes, resulting datasets that do not adequately represent testing In this study, we introduce comprehensive...

Significant changes in Land Use and Cover (LULC) have widespread implications for the environment, economy, society; influencing future sustainability development of a region. This study aimed to assess LULC 30 year period (1990 – 2020) project from 2030 2100 Irrawaddy Delta using remote sensing simulations with artificial neural networks-cellular automata method. The findings showed significant Delta, particularly mangrove forests cropland (rice paddies). Mangrove coverage was 1,471 km²...

Abstract Financial fraud activities are very frequent in recent days rural areas where people more need of money and desperate to make some any way possible. This research explores the nature, causes, consequences financial with impact on life responses law enforcement these occurrences. The primary data for this study was collected through in-depth interview from 24 victims fraud, 4 KIIs were conducted get semi-structured questionnaires using qualitative method, findings presented thematic...

Satellite-based remote sensing observations play an important role in retrieving soil moisture over the earth's surface. NASA's Cyclone Global Navigation Satellite System (CYGNSS) mission has gained attention as it uses (GNSS) Reflectometry (GNSS-R) which can provide higher spatial and temporal resolution. Research is going on to improve retrieval algorithms using CYGNSS observation. In addition observations, different land surface products are leveraged characterize underlying conditions....

A power system network generates, distributes and transmits the electricity.The reliable, as well safe systems, are very significant for successful operation.However, various losses faults occur in which prevents to work efficiently also causes damages.Overcurrent is a critical fault it results extreme production of heat, possibility fire or device damage, if not tripped timely.In order protect equipment from overcurrent, overcurrent relays were designed.In existing system, Inverse Definite...