Algorithm development on skin diseases identification with high cardinality classification is still very challenging. In addition, the high similarity appearance among diseases makes the computer vision approach meet ...
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information engineering strategies play a significant and transformative role in shaping the landscape of digital agriculture. It drives innovation and efficiency in modern farming practices, with a specific focus on ...
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ISBN:
(纸本)9798350304084
information engineering strategies play a significant and transformative role in shaping the landscape of digital agriculture. It drives innovation and efficiency in modern farming practices, with a specific focus on enhancing the value of agricultural commodities, such as sugarcane. The application of mobile technology plays a crucial part in achieving increased sugarcane productivity. Mobile applications, equipped with advanced developer features, offer rapid and user-friendly access to vital information. Traditional methods of estimating sugarcane production relied on manual data recording on paper, followed by data transfer to computer systems, typically managed by sugar factory junior plant officers. This conventional approach presents several inherent weaknesses, including time and effort intensiveness during data recording and entry. Additionally, the potential for errors in calculation and data input is a concern. The storage capacity for paper-based documents is finite, and farmers are often unable to autonomously assess their production potential. The objective of this research is to confront these obstacles by creating a sugarcane production application for Android. This application functions as an information engineering approach focused on forecasting sugarcane yields for plantation owners and their assistants. The development procedure adhered to the systematic waterfall method, following the principles of the Software Development Life Cycle (SDLC) model. Data collection was carried out through observations, while interviews with junior plant officers provided valuable insights into sugarcane estimation techniques. Analysis involved the synthesis of observational and interview data to inform the design of the application's interface and algorithmic system. The resulting application significantly simplifies the process of estimating production potential for farmers, enabling them to access sugarcane productivity data during harvest. Consequently, sugar
Universities can employ informationtechnology as one means of achieving their goals and objectives. Universities can get advantages from informationtechnology, such as effective resource management and information m...
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Emotion recognition in facial images is a topic that has attracted many interests. Research on emotion recognition in facial images continues to face challenges such as variations of human faces due to environments or...
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In this paper, we consider a scheduling issue for parcel delivery and pickup services by a truck-drone last-mile delivery system. We are given a single carrier truck and multiple identical drones to serve a finite set...
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The second-leading cause of cancer-related deaths globally is liver *** treatment of liver cancers depends heavily on the accurate segmentation of liver tumors from CT *** improved method based on U-Net has achieved g...
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The second-leading cause of cancer-related deaths globally is liver *** treatment of liver cancers depends heavily on the accurate segmentation of liver tumors from CT *** improved method based on U-Net has achieved good perfor-mance for liver tumor segmentation,but these methods can still be *** deal with the problems of poor performance from the original U-Net framework in the segmentation of small-sized liver tumors and the position information of tumors that is seriously lost in the down-sampling process,we propose the Multi-attention Perception-fusion U-Net(MAPFU-Net).We propose the Position ResBlock(PResBlock)in the encoder stage to promote the feature extraction capability of MAPFUNet while retaining the position information regarding liver tumors.A Dual-branch Attention Module(DWAM)is proposed in the skip connections,which narrows the semantic gap between the encoder's and decoder's features and enables the network to utilize the encoder's multi-stage and multi-scale *** propose the Channel-wise ASPP with Atten-tion(CAA)module at the bottleneck,which can be combined with multi-scale features and contributes to the recovery of micro-tumor feature ***,we evaluated MAPFUNet on the LITS2017 dataset and the 3DIRCADB-01 dataset,with Dice values of 85.81 and 83.84%for liver tumor segmentation,which were 2.89 and 7.89%higher than the baseline model,*** experiment results show that MAPFUNet is superior to other networks with better tumor feature representation and higher accuracy of liver tumor *** also extended MAPFUNet to brain tumor segmentation on the BraTS2019 *** results indicate that MAPFUNet performs well on the brain tumor segmentation task,and its Dice values on the three tumor regions are 83.27%(WT),84.77%(TC),and 76.98%(ET),respectively.
Semi-supervised learning (SSL) is a promising solution for the problem of insufficient medical labeled data. However, it is still a challenging task to segment transvaginal ultrasound (TVUS) images because of their po...
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The integration of 3D vision technology has profoundly impacted various aspects of our lives, with point clouds emerging as the predominant geometric representation in the field due to their simplicity, ease of proces...
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Multimodal Emotion Recognition in Conversation (ERC) is a task of predicting the emotion of each utterance in a conversation by utilizing both verbal and non-verbal modalities. However, existing approaches often strug...
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Every year, fire is responsible for numerous deaths, as well as huge material losses. Therefore, prevention and early detection of fire have become a priority for society, as well as the main research and development ...
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