Artificial intelligence is a field of computerscience dedicated to solving reasonable problems mostly associated with human intelligence such as pattern recognition and problem solving. This chapter proposes a projec...
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Self-driving and semi-self-driving cars play an important role in our daily *** effectiveness of these cars is based heavily on the use of their surrounding areas to collect sensitive and vital ***,external infrastruc...
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Self-driving and semi-self-driving cars play an important role in our daily *** effectiveness of these cars is based heavily on the use of their surrounding areas to collect sensitive and vital ***,external infrastructures also play significant roles in the transmission and reception of control data,cooperative awareness messages,and caution *** this case,roadside units are considered one of themost important communication *** distribution of these infrastructures will overburden the spread of self-driving vehicles in terms of cost,bandwidth,connectivity,and radio coverage *** this paper,a new distributed roadside unit is proposed to enhance the performance and connectivity of these ***,this approach is based primarily on k-means to find the optimal location of each roadside *** addition,this approach supports dynamicmobility with a long period of connectivity for each ***,this system can adapt to various locations(e.g.,highways,rural areas,urban environments).The simulation results of the proposed system are reflected in its efficiency and ***,the system can achieve a high connectivity rate with a low error rate while reducing costs.
Modi is an old script used for documentation in Maharashtra that dates to the 17th century. With time the writing style of the script changes, and a lot of variation occurred till date. In the 20th century, due to a l...
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Trained Artificial Intelligence (AI) models are challenging to install on edge devices as they are low in memory and computational power. Pruned AI (PAI) models are therefore needed with minimal degradation in perform...
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This study describes a broad endeavor to use cutting-edge technologies to empower deaf primary school students in Sri Lanka. Three key elements make up the study: a sound recognition and classification system, an Andr...
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This paper describes a speaker-attributed automatic speech recognition (SA-ASR) system submitted to the multi-channel multi-party meeting transcription challenge, which aims to address the "who spoke what" p...
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The sector of information compression and unsupervised feature getting to know has been gaining in recent years. A chief step forward in this location is the introduction of vehicle encoders, a neural network capable ...
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ISBN:
(纸本)9798350383348
The sector of information compression and unsupervised feature getting to know has been gaining in recent years. A chief step forward in this location is the introduction of vehicle encoders, a neural network capable of analyzing complex facts representations at a reduced dimensionality (i.e., feature studying). It has enabled various packages, from photograph compression, photograph inpainting, photograph category, and much more. This paper ambitions to discover and recognize the enhanced performance of car encoders compared to traditional dimensionality reduction and supervised getting-to-know strategies. Furthermore, the paper can even discuss the impact of using car encoders in the proposed framework to permit efficient, low latency, and robust compression abilities for actual-global issues. Furthermore, the chosen set of rules, its related model parameters, and the implementation information are furnished to analyze the impact of the usage of vehicle encoders for this assignment. Finally, the performance effects are discussed with applicable evaluaUnsupervised characteristic studying and compression with autoencoders (UFLACE), a practical machine studying approaches that may capture and constitute essential capabilities from high dimensional statistics in a compact shape. UFLACE allows training deep neural networks with constrained education statistics and computational assets. Compared to different unsupervised function getting-to-know methods, UFLACE has verified demonstrable increased overall performance in phrases of type accuracy and reconstruction great. It comes from the capability of UFLACE to examine more complex representations of the dataset in some layers, mainly to improve compression of the statistics and a greater correct and robust class. Using UFLACE additionally eliminates over-fitting troubles and provides improved generalization capability, resulting in higher standard performance of the model. Additionally, UFLACE may be used for informatio
As social media platforms continue to expand, understanding user behavior and emotions has become essential. This paper introduces a framework for creating detailed user profiles by analyzing the sentiments expressed ...
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The threat posed by phishing websites is significant in the digital era due to the widespread use of online activities, which has prompted the need for a comprehensive remedy. The project involves building a website t...
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This research addresses the critical need for early crop disease detection to optimize yields and minimize economic losses. Leveraging DenseNet, a deep learning model, the study focuses on automated detection of rice ...
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