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Ensemble of Handcrafted and Deep Learning Model for Histopathological Image Classification

Computers, Materials & Continua 2022年第11期73卷 4393-4406页

作者： Vasumathi Devi Majety N.Sharmili chinmaya ranjan pattanaik ELaxmi Lydia Subhi R.M.Zeebaree Sarmad Nozad Mahmood Ali S.Abosinnee Ahmed Alkhayyat Department of Computer Science Engineering Vignan’s Nirula Institute of Technology and Science for WomenGuntur522005India Department of Computer Science Engineering Gayatri Vidya Parishad College of Engineering for WomenVisakhapatnam530048India Department of Computer Science and Engineering Ajay Binay Institute of Technology CuttackOdisha750314India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Energy Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq Computer Technology Engineering College of Engineering TechnologyAl-Kitab UniversityIraq Computer Technical Engineering Department College of Technical EngineeringThe Islamic UniversityNajaf54001Iraq College of Technical Engineering The Islamic UniversityNajafIraq

Histopathology is the investigation of tissues to identify the symptom of *** histopathological procedure comprises gathering samples of cells/tissues,setting them on the microscopic slides,and staining *** investigation of the histopathological image is a problematic and laborious process that necessitates the expert’s *** the same time,deep learning(DL)techniques are able to derive features,extract data,and learn advanced abstract data *** this view,this paper presents an ensemble of handcrafted with deep learning enabled histopathological image classification(EHCDL-HIC)*** proposed EHCDLHIC technique initially performs Weiner filtering based noise removal *** the images get smoothened,an ensemble of deep features and local binary pattern(LBP)features are *** the classification process,the bidirectional gated recurrent unit(BGRU)model can be *** the final stage,the bacterial foraging optimization(BFO)algorithm is utilized for optimal hyperparameter tuning process which leads to improved classification performance,shows the novelty of the *** validating the enhanced execution of the proposed EHCDL-HIC method,a set of simulations is *** experimentation outcomes highlighted the betterment of the EHCDL-HIC approach over the existing techniques with maximum accuracy of 94.78%.Therefore,the EHCDL-HIC model can be applied as an effective approach for histopathological image classification.

关键词： Histopathological image classification machine learning deep learning handcrafted features bacterial foraging optimization

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Agromorphological and Molecular Characterization of Sesamum indicum L.—An Oil Seed Crop

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American Journal of Plant Sciences 2016年第17期7卷 2399-2411页

作者： Tapaswini Hota chinmaya Pradhan Gyana ranjan Rout Department of Agricultural Biotechnology College of Agriculture OUAT Bhubaneswar India Post Graduate Department of Botany Utkal University Bhubaneswar India

Sesamum indicum L. (family: Pedaliaceae) is an economically important oil seed crop grown in tropical and sub-tropical countries. It is widely used in food, nutraceutical, pharmaceutical industries. Sesamum is widely distributed in all the climatic stages and great diversity. The exploration of genetic diversity is a pre-requisite for genome organization in the landraces and the related domesticated ones. Agromorphological and molecular markers were used to assess the identification of 33 Sesamum genotypes and determination of the genetic relationships among these genotypes. Out of 30 Inter-Simple Sequence Repeat (ISSR) primers tested, 18 primers produced 114 detectable fragments, of which 97 (85.08%) were polymorphic across the varieties. Molecular profiling could be solely used for their identification of genotypes. Genetic relationships among these genotypes were evaluated by generating a similarity matrix based on the Jacard’s coefficient and the Unweighted Pair Group Method with Arithmetic Average (UPGMA) dendogram. The results showed a clear cut separation of the 33 genotypes and were in broad agreement with the morphology. Both molecular and morphological markers will be useful for preservation of the germplasm as well as breeding program.

关键词： Sesamum PCR Based Marker Phylogeny Molecular Profiling Agro-Mophological Traits

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Carbon and water footprints of major crop production in India

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Pedosphere 2023年第3期33卷 448-462页

作者： Amaresh Kumar NAYAK Rahul TRIPATHI Manish DEBNATH chinmaya Kumar SWAIN Biswaranjan DHAL Shanmugam VIJAYKUMAR Anshuman Debasis NAYAK Sangita MOHANTY Mohammad SHAHID Anjani KUMAR Manoj RAJAK Khitish Chandra MOHARANA Dibyendu CHATTERJEE Susmita MUNDA Pravat GURU Rubina KHANAM Banwari LAL Priyanka GAUTAM Suschismita pattanaik Arvind Kumar SHUKLA Nuala FITTON Pete SMITH Himanshu PATHAK Indian Council of Agriculture Research(ICAR)-National Rice Research Institute Cuttack 753006(India) ICAR-Central Sheep and Wool Research Institute Avikanagar 304501(India) ICAR-National Research Centre on Camel Bikaner 304001(India) ICAR-Indian Institute of Soil Science Bhopal 462038(India) Institute of Biological and Environmental Sciences University of Aberdeen23St Machar DriveAberdeen AB243UU(UK)

Scarcity of water and emission of greenhouse gases(GHGs)are the two key environmental issues affecting crop production in *** the carbon footprint(CF)and water footprint(WF)of crop production can help to mitigate the environmental hazards that stem from GHG emissions and water *** CFs and WFs of three major cereal crops,rice,wheat,and maize,were estimated for the year 2014 under the environmental conditions in India,based on national statistics and other data *** CFs(TCFs)of rice,wheat,and maize in India were estimated to be 2.44,1.27,and 0.80 t CO_(2)equivalent ha-1,respectively,and product WFs for rice,wheat,and maize in India were 3.52,1.59,and 2.06 m3 kg^(-1),*** WF was found to be the highest in West India for rice and in South India for both wheat and maize,with the highest irrigation water use in these *** was a positive correlation between TCF and total WF,and hence mitigation of both was possibly simultaneous in various regions in *** measures for mitigating GHG emissions and optimizing water use for rice,wheat,and maize production in India are recommended in this paper.

关键词： cereal crop crop planning green water footprint greenhouse gas emission water productivity water use

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