A real-world information extraction (IE) system for semi-structured document images often involves a long pipeline of multiple modules, whose complexity dramatically increases its development and maintenance cost. One can instead consider an end-to-e
nd model that directly maps the input to the target output and simplify the entire process. However, such generation approach is known to lead to unstable performance if not designed carefully. Here we present our recent effort on transitioning from our existing pipeline-based IE system to an end-to-end system focusing on practical challenges that are associated with replacing and deploying the system in real, large-scale production. By carefully formulating document IE as a sequence generation task, we show that a single end-to-end IE system can be built and still achieve competent performance.
We describe our approach for SemEval-2021 task 6 on detection of persuasion techniques in multimodal content (memes). Our system combines pretrained multimodal models (CLIP) and chained classifiers. Also, we propose to enrich the data by a data augmentation technique. Our submission achieves a rank of 8/16 in terms of F1-micro and 9/16 with F1-macro on the test set.
The amount of digital images that are produced in hospitals is increasing rapidly. Effective
medical images can play an important role in aiding in diagnosis and treatment, they can
also be useful in the education domain for healthcare students by
explaining with these
images will help them in their studies, new trends for image retrieval using automatic
image classification has been investigated for the past few years. Medical image
Classification can play an important role in diagnostic and teaching purposes in medicine.
For these purposes different imaging modalities are used. There are many classifications
created for medical images using both grey-scale and color medical images. In this paper,
different algorithms in every step involved in medical image processing have been studied.
One way is the algorithms of preprocessing step such as Median filter [1], Histogram
equalization (HE) [2], Dynamic histogram equalization (DHE), and Contrast Limited
Adaptive Histogram Equalization (CLAHE). Second way is the Feature Selection and
Extraction step [3,4], such as Gray Level Co-occurrence Matrix(GLCM). Third way is the
classification techniques step, which is divided into three ways in this paper, first one is
texture classification techniques, second one is neural network classification techniques,
and the third one is K-Nearest Neighbor classification techniques.
In this paper, we have use MRI brain image to determine the area of tumor in brain. The
steps started by preprocessing operation to the image before inputting it to algorithm. The
image was converted to gray scale, later on remove film artifact using special algorithm,
and then remove the Skull portions from the image without effect on white and gray matter
of the brain using another algorithm, After that the image enhanced using optimized
median filter algorithm and remove Impurities that produced from first and second steps.
The Histogram of Oriented Gradient
(HOG) was used to construct the Support Vector Machine (SVM)
workbook. This method was applied using C++ programming
language and OpenCV and Dlib Libraries.
The science and art of producing maps had been subjected to the changes as a result
of new recent techniques developments at space photogrammetry, that lead to appearance
of programs and applications in the computer's world. This associated with th
e advent of
information age and Geographic information system that changed the traditional
topographic map from just a map to an analyzing and viewing tool.
All Syrian Topographic maps are old, out dated, and largely exist in paper form. Due
to the high cost of aerial photography, These maps have not been updated for many years
and such are not useful for planning. Therefore, there is an urgent need to produce new
maps using high resolution satellite images.
The research put a method for updating topographic maps of Al-Bahlolia district
which have scales (1/50000) and (1/200000), By using Cartosat1 images.
After updating, The results were that there is increasing in the area of planted land. In
addition to building developments, increasing of length and density of roads between and
inside villages. Contour lines also have been generated automatically, so efforts and time
were be saved.
Digital Elevation Model
Satellite Images
الخرائط الطبوغرافية
المرئيات الفضائية
برنامج نموذج الارتفاع الرقمي
برنامج خاص بتطبيقات المساحة التصويرية
بمعالجة المرئيات الفضائية
التوجيه الداخلي و الخارجي
بناء الطبقات الهرمية
التصحيح العمودي
Topographic maps
(Leica Photogrammetry (LPS
Erdas Imagine
Interior and Exterior Orientation
Compute Pyramids
Ortho Rectification
المزيد..
In this study, SST satellite images analysis (from
September 2015 to November 2016) is focalised on the
monitoring of the mesoscale eddies in the eastern Levantine subbasin
(at the Syrian coasts as well as the neighboring coasts).
Considering the increasing importance of stereo image compression and Fractal
geometry becoming one of the most important fields of modern science ,we applied fractal
image compression based on quadtree portioning method and global search algorithm
, on
a group of stereo image pairs . As the stereo image consists of two planar images , left and
right .Both the left image ( reference image ) and the disparity map between left and right
images , were compressed using fractal compression . We applied both block matching
algorithm and Semi Global Method (SGM)to obtain the disparity map.
The left image and the depth map were reconstructed using fractal decompression
while the right image (target image ) was reconstructed using the reconstructed left image ,
disparity map and the error image between the original right image and the reconstructed
right image that was build from the left image and the disparity map .
The results were evaluated using quality objective measures which are MSE (Mean
Square Error ) and PSNR (Peak Signal to Noise Ratio) and efficiency objective measures
which are CR(Compression Ratio) and compression time . The results were compared
with JPEG compression of stereo pairs based on Discrete Cosine Transform DCT and
JPEG2000 compression of stereo pairs on stereo image based on Discrete Wavelet
Transform DWT .
In this paper, we processed an array which represents the
human hand image to get the characteristics of this image. So,
we used FPGA technique, and the processing operation is
partitioned into three threads which is carried out in parallel.
Each
thread is carried out using the pipeline technique by
partitioning thread into four segments. After that, we evaluated
the speedup that we get in result of using the pipeline technique
and the parallel threads. So, we have the possibility to design an
embedded system integrated into chip (SoC), and using the
mobile phones as integral devices support the software and
hardware resources.
معالجة الصور
إيماءات الصم و البكم
تعرف على الأشكال
معالجة أنبوبية
مسالك
معالجة تفرعية
دارات قابلة للبرمجة
لغة توصيف مادية
نظام مضمن
نظام ضمن شريحة
تسريع
Deaf and Mute Gestures
Images Processing
Patterns Recognition
Pipeline Processing
Threads
Parallel Processing
(Programmable Circuits (FPGA
(Hardware Description Language (VHDL
(System on Chip (SoC
المزيد..
In this paper, we
describe an algorithm to register the retinal images by employing a relatively
cross-correlation function. Pixel to pixel accuracy has been investigated and
evaluated among registered images by calculating the local cross-correla
tion
between extracted vessels profiles along tracked vessels after transforming
the images into alignment.
This Paper offers an effective method to measure the length of the
femur in Fetal Ultrasound Images, it applies a series of steps
starting with the reducing amount of noise in these images, and
then converted them to a binary form and uses morphol
ogical
operations to segment the femur and isolate it from the rest of the
image objects, then it applies an Edge Detector in order to find the
edges of the bone, then uses the Hough Transform to detect straight
lines in the image. we apply overlapping for resulted lines on the
original image, finally we choose the most significant and longest
straight line which is corresponding to the length of the femur. The
proposed method facilitates the measurement of the femur without
the help of a physician through a series of steps.