In recent years wireless sensor networks have helped with automation in many industry domains. Wireless technology cuts cable costs, deployment time and information to transfer and process from source to destination. ...
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The FOD-R Dataset is a collection of images that depict common types of foreign object debris (FOD) that can be found on runways or taxiways. The dataset has primarily been annotated using bounding boxes to facilitate...
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Cardiovascular disease (CVD) remains a significant global health concern, necessitating early detection and accurate prediction for effective intervention. Machine learning (ML) offers a data-driven approach to analyz...
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Progressive technological development results in modern automotive technology such as self-driving automobiles. These require sensors to collect data about nearby objects and the surroundings in order to identify lane...
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In current scenario, we have multiple technologies are available to transmit the data in wireless ad hoc network (WANET).But, compare to other existing models, we have proposed a new model where not only this model he...
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TB has been considered to be a major global health hazard. With regard to early meningitis tuberculosis identification, numerous studies and research have been conducted in recent years. The most serious form of tuber...
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Speech analysis has emerged as a crucial tool in bridging the gap between the real and virtual worlds as the amount of human contact with machines increases. One subfield that has long been investigated in both psychi...
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This research study intends to explore various challenges that humans have encountered as well as any that may arise in the near future. Poor sanitation facility is one of the main causes of malnutrition and it leads ...
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Unwanted plants called weeds commonly appear among crops. These weeds have the potential to drastically lower farm output yield and quality. Unfortunately, most of the time, site-specific weed management is not implem...
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Unwanted plants called weeds commonly appear among crops. These weeds have the potential to drastically lower farm output yield and quality. Unfortunately, most of the time, site-specific weed management is not implemented. This means that a field is treated with a broadcast herbicide spray rather than a specific type of herbicide. Herbicide-resistant weeds have developed as a result of this herbicide's widespread use, which has various negative effects on the environment. This has led to numerous research investigations looking for the best weed control methods. computer vision-based automatic weed detection and identification is one such method. With the help of this method, weeds may be located and identified, and farmers can be advised to use a certain herbicide. Consequently, it's crucial that the correctly recognise and categorise the crops and weeds from the digital photos using a computer vision technology. Deep learning, a type of artificial intelligence, is a rapidly expanding research area at the moment. Its many uses, which incorporate computer vision, include object recognition. The goal of this effort is achieved by combining these two technologies. As an alternative to the system used in the literature, a system for the identification of various crops and weeds has been devised in this research. Digital pictures of the crops and weeds growing in the fields were taken using three separate cameras that were mounted at varied heights from the ground. Digital image properties like texture, colour, and shape were retrieved after the backdrop was removed and used for classification. To accomplish this, access computer vision is utilised to process images, and artificial intelligence is employed to apply transfer learning to an RCNN that automatically recognises plants. The method has an accuracy of 78.10% for the main crop and 53.12% and 44.76% for the two weeds under consideration, according to the results. The coordinates of the weeds are also included in
During corn's exploration and manufacturing phases, farmers have a complicated issue in accurately diagnosing corn crop infections. To solve this issue, this work provides a method for specific position three prev...
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