|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | 棉花黄萎病菌致病类型及其分子指纹分析显示文摘对20个大丽轮枝菌菌株的致病性进行了测定和RAPD指纹扩增,完成了供试菌株致病类群与其RAPD指纹组间的相关性分析。结果表明,根据20个菌株对5个棉花品种的抗感反应及其平均病情指数分为4种不同的致病类群;用10个随机引物对20个菌株进行RAPD-PCR扩增,产生92条DNA带(其中51条为多态带);用计算机进行聚类分析,20个供试菌株聚类为9个RAPD指纹组。相关性分析表明,致病类群与RAPD指纹组无明显相关性;但与部分单引物扩增的RAPD谱型有明显对应关系,如引物OPC-15随机扩增的RAPD谱型,除致病类群VG3的菌株外,其余致病类群均有对应的RAPD指纹谱带;其它引物(OPC-05,OPM-13,OPA-02,OPL-02)也有相似的结果。 | 朱有勇 王云月 Dilbag S.M. Bruce R.L. | 1998 | 中国农业科学1998，31，3： | 15 |
| 2 | Single image defogging by gain gradient image filter显示文摘Dear editor,With the advancements in computer vision applications, the image defogging methods have received a lot of consideration. Defogging methods are extensively utilized in civil and military areas such as target detection, traffic surveillance,remote sensing. | Dilbag SINGH Vijay KUMAR | 2019 | Science China(Information Sciences)2019，62，7： | 5 |
| 3 | QRS detection using K -Nearest Neighbor algorithm (KNN) and evaluation on standard ECG databases显示文摘 | Indu Saini Dilbag Singh Arun Khosla | 2013 | Journal of Advanced Research2013，，4： | 2 |
| 4 | Loss of an MDR Transporter in Compact Stalks of Maize br2 and Sorghum dw3 Mutants 显示文摘 | Dilbag S Multani Steven P Briggs Mark A Chamberlin | 2003 | Science2003，302，： | 1 |
| 5 | A surface roughness prediction model for hard turning process显示文摘 | Dilbag Singh P. Venkateswara Rao | 2007 | The International Journal of Advanced Manufacturing Technology2007，，11： | 1 |
| 6 | Loss of an MDR transporter in compact stalks of maize br2 and sorghum dw3 mutants 显示文摘 | Dilbag S M Steven P B Mark A C | 2003 | Science2003，302，3： | 1 |
| 7 | A surface roughness prediction model for hard turning process显示文摘 | Dilbag Singh P. Venkateswara Rao | 2007 | The International Journal of Advanced Manufacturing Technology (-)2007，，11： | 1 |
| 8 | A surface roughness prediction model-for hard turning process显示文摘 | DILBAG S RAO P V | 2007 | Int J Adv Manuf Technol2007，32，： | 1 |
| 9 | A Surface Roughness Prediction Model for Hard Turning Process 显示文摘 | SINGH Dilbag RAO P Venkateswara | 2007 | Int J Adv Manuf Technol2007，32，1112： | 1 |
| 10 | Detection method and filters for blocking effect reduction of highly compressed images显示文摘 | Jagroop S Sukhwinder S Dilbag S | 2011 | Signal Processing: Im- age Communication2011，26，8： | 1 |
| 11 | A Novel Hybrid Tunicate Swarm Naked Mole-Rat Algorithm for Image Segmentation and Numerical Optimization显示文摘This paper provides a new optimization algorithm named as tunicate swarm naked mole-rat algorithm(TSNMRA)which uses hybridization concept of tunicate swarm algorithm(TSA)and naked mole-rat algorithm(NMRA).This newly developed algorithm uses the characteristics of both algorithms(TSA and NMRA)and enhance the exploration abilities of NMRA.Apart from the hybridization concept,important parameter of NMRA such as mating factor is made to be self-adaptive with the help of simulated annealing(sa)mutation operator and there is no need to define its value manually.For evaluating the working capabilities of proposed TSNMRA,it is tested for 100-digit challenge(CEC 2019)test problems and real multi-level image segmentation problem.From the results obtained for CEC 2019 test problems,it can be seen that proposed TSNMRA performs well as compared to original TSA and NMRA.In case of image segmentation problem,comparison of TSNMRA is performed with multi-threshold electro magnetism-like optimization(MTEMO),particle swarm optimization(PSO),genetic algorithm(GA),bacterial foraging(BF)and found superior results for TSNMRA. | Supreet Singh Nitin Mittal Urvinder Singh Rohit Salgotra Atef Zaguia Dilbag Singh | 2022 | Computers, Materials & Continua2022，，5： | 0 |
| 12 | A Post-Processing Algorithm for Boosting Contrast of MRI Images显示文摘Low contrast of Magnetic Resonance(MR)images limits the visibility of subtle structures and adversely affects the outcome of both subjective and automated diagnosis.State-of-the-art contrast boosting techniques intolerably alter inherent features of MR images.Drastic changes in brightness features,induced by post-processing are not appreciated in medical imaging as the grey level values have certain diagnostic meanings.To overcome these issues this paper proposes an algorithm that enhance the contrast of MR images while preserving the underlying features as well.This method termed as Power-law and Logarithmic Modification-based Histogram Equalization(PLMHE)partitions the histogram of the image into two sub histograms after a power-law transformation and a log compression.After a modification intended for improving the dispersion of the sub-histograms and subsequent normalization,cumulative histograms are computed.Enhanced grey level values are computed from the resultant cumulative histograms.The performance of the PLMHE algorithm is comparedwith traditional histogram equalization based algorithms and it has been observed from the results that PLMHE can boost the image contrast without causing dynamic range compression,a significant change in mean brightness,and contrast-overshoot. | B.Priestly Shan O.Jeba Shiney Sharzeel Saleem V.Rajinikanth Atef Zaguia Dilbag Singh | 2022 | Computers, Materials & Continua2022，，8： | 0 |
| 13 | DWT-SVD Based Image Steganography Using Threshold Value Encryption Method显示文摘Digital image steganography technique based on hiding the secret data behind of cover image in such a way that it is not detected by the human visual system.This paper presents an image scrambling method that is very useful for grayscale secret images.In this method,the secret image decomposes in three parts based on the pixel’s threshold value.The division of the color image into three parts is very easy based on the color channel but in the grayscale image,it is difficult to implement.The proposed image scrambling method is implemented in image steganography using discrete wavelet transform(DWT),singular value decomposition(SVD),and sorting function.There is no visual difference between the stego image and the cover image.The extracted secret image is also similar to the original secret image.The proposed algorithm outcome is compared with the existed image steganography techniques.The comparative results show the strength of the proposed technique. | Jyoti Khandelwal Vijay Kumar Sharma Dilbag Singh Atef Zaguia | 2022 | Computers, Materials & Continua2022，，8： | 0 |
| 14 | Image Segmentation Based on Block Level and Hybrid Directional Local Extrema显示文摘In the recent decade,the digitalization of various tasks has added great flexibility to human lifestyle and has changed daily routine activities of communities.Image segmentation is a key step in digitalization.Segmentation plays a key role in almost all areas of image processing,and various approaches have been proposed for image segmentation.In this paper,a novel approach is proposed for image segmentation using a nonuniform adaptive strategy.Region-based image segmentation along with a directional binary pattern generated a better segmented image.An adaptive mask of 8×8 was circulated over the pixels whose bit value was 1 in the generated directional binary pattern.Segmentation was performed in three phases:first,an image was divided into sub-images or image chunks;next,the image patches were taken as input,and an adaptive threshold was generated;and finally the image chunks were processed separately by convolving the adaptive mask on the image chunks.Gradient and Laplacian of Gaussian algorithms along with directional extrema patterns provided a double check for boundary pixels.The proposed approach was tested on chunks of varying sizes,and after multiple iterations,it was found that a block size of 8×8 performs better than other chunks or block sizes.The accuracy of the segmentation technique was measured in terms of the count of ill regions,which were extracted after the segmentation process. | Ghanshyam Raghuwanshi Yogesh Gupta Deepak Sinwar Dilbag Singh Usman Tariq Muhammad Attique Kuntha Pin Yunyoung Nam | 2022 | Computers, Materials & Continua2022，，2： | 0 |
| 15 | Screening of COVID-19 Patients Using Deep Learning and IoT Framework显示文摘In March 2020,the World Health Organization declared the coronavirus disease(COVID-19)outbreak as a pandemic due to its uncontrolled global spread.Reverse transcription polymerase chain reaction is a laboratory test that is widely used for the diagnosis of this deadly disease.However,the limited availability of testing kits and qualified staff and the drastically increasing number of cases have hampered massive testing.To handle COVID19 testing problems,we apply the Internet of Things and artificial intelligence to achieve self-adaptive,secure,and fast resource allocation,real-time tracking,remote screening,and patient monitoring.In addition,we implement a cloud platform for efficient spectrum utilization.Thus,we propose a cloudbased intelligent system for remote COVID-19 screening using cognitiveradio-based Internet of Things and deep learning.Specifically,a deep learning technique recognizes radiographic patterns in chest computed tomography(CT)scans.To this end,contrast-limited adaptive histogram equalization is applied to an input CT scan followed by bilateral filtering to enhance the spatial quality.The image quality assessment of the CT scan is performed using the blind/referenceless image spatial quality evaluator.Then,a deep transfer learning model,VGG-16,is trained to diagnose a suspected CT scan as either COVID-19 positive or negative.Experimental results demonstrate that the proposed VGG-16 model outperforms existing COVID-19 screening models regarding accuracy,sensitivity,and specificity.The results obtained from the proposed system can be verified by doctors and sent to remote places through the Internet. | Harshit Kaushik Dilbag Singh Shailendra Tiwari Manjit Kaur Chang-Won Jeong Yunyoung Nam Muhammad Attique Khan | 2021 | Computers, Materials & Continua2021，，12： | 0 |
| 16 | Safest Route Detection via Danger Index Calculation and K-Means Clustering显示文摘The study aims to formulate a solution for identifying the safest route between any two inputted Geographical locations.Using the New York City dataset,which provides us with location tagged crime statistics;we are implementing different clustering algorithms and analysed the results comparatively to discover the best-suited one.The results unveil the fact that the K-Means algorithm best suits for our needs and delivered the best results.Moreover,a comparative analysis has been performed among various clustering techniques to obtain best results.we compared all the achieved results and using the conclusions we have developed a user-friendly application to provide safe route to users.The successful implementation would hopefully aid us to curb the ever-increasing crime rates;as it aims to provide the user with a beforehand knowledge of the route they are about to take.A warning that the path is marked high on danger index would convey the basic hint for the user to decide which path to prefer.Thus,addressing a social problem which needs to be eradicated from our modern era. | Isha Puthige Kartikay Bansal Chahat Bindra Mahekk Kapur Dilbag Singh Vipul Kumar Mishra Apeksha Aggarwal Jinhee Lee Byeong-Gwon Kang Yunyoung Nam Reham R.Mostafa | 2021 | Computers, Materials & Continua2021，，11： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员