Pirithous
Multi tool use
Vide etiam paginam discretivam: Pirithous (discretiva)
Centaurus quidam Hippodamian rapit : Pirithous et Theseus armati succurunt ad eam defendendam. Crater rubentibus figuris ex Apulia, hodie in Museo Britannico. Medio quarto saeculo a.C.n.
Pirithous (Graece Πειρίθοος) in mythologia Graeca fuit rex Lapitharum, filius Ixionis et Diae, amicus Thesei et maritus Hippodamiae, Adrasti filiae.
Multis audacibus inceptis cum ceteris ducibus Graeciae interfuit, ut Argonautarum expeditioni vel apri Calydonii venationi. Ad nuptias suas semifratres (nam filii Ixionis erant et ipsi) centauros invitavit. Qui vero ebrii facti novam uxorem Hippodamian et ceteras mulieres rapere et comprimere voluerunt. A quo magna pugna cum Lapithis oborta est, cuius victoriam Theseus et Pirithous rettulerunt. Haec rixa persaepe in signis vel in vasis ab antiquis artificibus expressa est. Postea insana audacia actus Proserpinam, uxorem Plutonis rapere et in lucem solis trahere voluit. Itaque cum amico Theseo ad Inferos descendit, ubi a rege umbrarum exceptus adfixus saxo est nec umquam postea lumen solis vidit nec in terras rediit. Nam cum Hercules in Plutonis regnum et ipse descendit, secum Theseum ad ripas lucis reduxit, Pirithoum vero non potuit.
Fontes |
Apollodori bibliotheca 2.5.12, etc.
Homerus, Odyssea XXI, 295-305, XI, 631
Hyginus mythographus Fabulae 14,33,79,257.
Ovidius, Metamorphoses VIII,303 et XII.218
Vergilius, Aeneis VI.393.
Nexus externi |
|
Vicimedia Communia plura habent quae ad Pirithoum spectant.
|
.mw-parser-output .stipula{padding:3px;background:#F7F8FF;border:1px solid grey;margin:auto}.mw-parser-output .stipula td.cell1{background:transparent;color:white}
|
Haec stipula ad mythologiam spectat. Amplifica, si potes!
|
j83UqKA1l7wshaRZT5,Y,l4iU
Popular posts from this blog
Tabula multilinguis Rosettana in Museo Britannico ostenditur. Tabula Rosettana, [1] etiam titulo OGIS 90 agnita, est stela decreto de rebus sacris in Aegypto anno 196 a.C.n. lato inscripta. Tabula iuxta Rosettam Aegypti, urbem in delta Nili et ad oram maris Mediterranei iacentem, anno 1799 a milite Francico reperta est. Inventio stelae, linguis duabus scripturisque tribus inscriptae, eruditis Instituti Aegypti statim nuntiata est; ibi enim iussu imperatoris Napoleonis eruditi omnium scientiarum (sub aegide Commissionis Scientiarum et Artium) properaverant cum expeditione Francica. Qua a Britannis mox debellata, tabula Rosettana Londinium missa hodie apud Museum Britannicum iacet. Textus Graecus cito lectus interpretationi textuum Aegyptiorum (in formis hieroglyphica et demotica expressorum) gradatim adiuvit. Denique textum plene interpretatus est Ioannes Franciscus Champollion. Ab opere eruditorum cumulativo coepit hodiernus scripturae hieroglyphicae linguaeque Aegyptiae a...
1
$begingroup$
This is what I mean as document text image: I want to label the texts in image as separate blocks and my model should detect these labels as classes. NOTE: This is how the end result should be like: The labels like Block 1, Block 2, Block 3,.. should be Logo, Title, Date,.. Others, etc. Work done: First approach : I tried to implement this method via Object Detection, it didn't work. It didn't even detect any text. Second approach : Then I tried it using PixelLink. As this model is build for scene text detection, it detected each and every text in the image. But this method can detect multiple lines of text if the threshold values are increased. But I have no idea how do I add labels to the text blocks. PIXEL_CLS_WEIGHT_all_ones = 'PIXEL_CLS_WEIGHT_all_ones' PIXEL_C...
1
$begingroup$
I have this LSTM model model = Sequential() model.add(Masking(mask_value=0, input_shape=(timesteps, features))) model.add(LSTM(100, dropout=0.2, recurrent_dropout=0.2, return_sequences=False)) model.add(Dense(features, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy']) and shapes X_train (21, 11, 5), y_train (21, 5) . Each timestep is represented by 5 features and return_sequences is set to False because I want to predict one 5D array (the next timestep) for each input sequence of 11 timesteps. I get the error ValueError: y_true and y_pred have different number of output (5!=1) If I reshape the data as X_train (21, 11, 5), y_train (21, 1, 5) instead I get the error ValueError: Inva...
